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Statistical Consulting
Mathematics Learning Center
Research
Mathematical Bioscience
A wide variety of interdisciplinary research into mathematical and statistical aspects of the biosciences is conducted at UC. Our Mathematical Biology group studies mathematical modeling of complex physical phenomena. Don French studies numerical and computational models in neuroscience in collaboration with colleagues from the College of Medicine. Tony Leung studies problems in partial differential equations related to ecology and population dynamics. Sookkyung Lim uses scientific computation to study valveless pumping and flagellar movement. Steve Pelikan works in evolutionary genetics in collaboration with Steve Rogstadt from the Department of Biology.
Our statisticians work closely with colleagues researchers in medicine and environmental health on various aspects of biostatsitics.Jim Deddens current interest is in developing statistical methodology in quantitative occupational epidemiology. For several years he has been collaborating with researchers at the National Institute for Occupational Safety and Health (NIOSH) on cancer mortality and ergonomic studies. Siva Sivaganesan works with colleagues at Children's Hospital and the Department of Environmental Health on applications of Bayesian Statistics. Paul Horn recently coauthored a book on the use of reference intervals in medicine. Xiaodong Lin's interests include statistical problems in medical imaging
FacultyMathematical modeling
Don French, computational neuroscience, finite element methods, finite difference methods.
Sookkyung Lim, scientific computation, valveless pumping, flagellar movement.
Anthony Leung, population dynamics, ecological and biological models.
Stephan Pelikan, biomathematics, population genetics and structure.
Biostatistics
Jim Deddens, biostatistics, quantitative epidemiology.
Paul Horn, robustness, non-parametric methods, ROC analysis, chemical trials.
Xiaodong Lin, Bioinformatics, statistical learning theory, privacy preserving statistical analysis, mixture models, medical imaging.
Siva Sivaganesan , Bayesian statistics.
Seongho Song, Bayesian analysis, population genetics